Sensitivity Analysis of the Artificial Neural Network Outputs in Friction Stir Lap Joining of Aluminum to Brass
Joint Authors
Akbari, Mostafa
Shojaeefard, Mohammad Hasan
Farhani, Foad
Tahani, Mojtaba
Source
Advances in Materials Science and Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-03-21
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Engineering Sciences and Information Technology
Abstract EN
Al-Mg and CuZn34 alloys were lap joined using friction stir welding while the aluminum alloy sheet was placed on the CuZn34.
In addition, the mechanical properties of each sample were characterized using shear tests.
Scanning electron microscopy (SEM) and X-ray diffraction analysis were used to probe chemical compositions.
An artificial neural network model was developed to simulate the correlation between the Friction Stir Lap Welding (FSLW) parameters and mechanical properties.
Subsequently, a sensitivity analysis was performed to investigate the effect of each input parameter on the output in terms of magnitude and direction.
Four methods, namely, the “PaD” method, the “Weights” method, the “Profile” method, and the “backward stepwise” method, which can give the relative contribution and/or the contribution profile of the input factors, were compared.
The PaD method, giving the most complete results, was found to be the most useful, followed by the Profile method that gave the contribution profile of the input variables.
American Psychological Association (APA)
Shojaeefard, Mohammad Hasan& Akbari, Mostafa& Tahani, Mojtaba& Farhani, Foad. 2013. Sensitivity Analysis of the Artificial Neural Network Outputs in Friction Stir Lap Joining of Aluminum to Brass. Advances in Materials Science and Engineering،Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-481991
Modern Language Association (MLA)
Shojaeefard, Mohammad Hasan…[et al.]. Sensitivity Analysis of the Artificial Neural Network Outputs in Friction Stir Lap Joining of Aluminum to Brass. Advances in Materials Science and Engineering No. 2013 (2013), pp.1-7.
https://search.emarefa.net/detail/BIM-481991
American Medical Association (AMA)
Shojaeefard, Mohammad Hasan& Akbari, Mostafa& Tahani, Mojtaba& Farhani, Foad. Sensitivity Analysis of the Artificial Neural Network Outputs in Friction Stir Lap Joining of Aluminum to Brass. Advances in Materials Science and Engineering. 2013. Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-481991
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-481991